MeDIAuto

MeDIAuto is a multi-viewer solution that can view pathology WSI data in various formats.

Multi-functional viewer

• Standardizing different image data formats from scanner manufacturers
• Conveniently converting WSI (TIFF format) files to JPEG and adding annotations

Convenient interface

• Easily annotate large clinical WSI with zoom and rotate features for quick and convenient annotation.

Cloud-based

• Start directly in the Chrome browser environment without the need for plugin installation
• Standardize high-resolution large images in TIFF format and downsize them for uploading to the cloud, addressing storage issues.

Workflow improvement

• Quality management functions for labeling and inspection in a dashboard format, project-specific task and organization-based performance management.
• Efficient management of progress through statistical functions for cancer-specific projects with a large volume of data and a workforce involved.

To read more please go to: https://mediauto.urbandatalab.co.kr/

MeDIAuto is a web-based platform that allows you to easily manage learning data to improve the performance of digital pathology artificial intelligence models.

• Provides multi-project management functions and user, dataset, and label set management functions for each project.
• Supports various formats (ndpi, svs, tiff, bif etc.) of whole slide image.
• For standardized learning data image management, a conversion management function to generic-tiff is provided.
• Supports data labeling with various annotation type tools.
• Supports inspection function for annotation processing work. (Annotation → Review → Termination)
• Provides a dashboard for each project that allows you to intuitively understand the current data processing progress.
• Auto labeling function can be added using the learned artificial intelligence model.

< Associated with AWS >

EC2: An instance with customizable instance type & EBS disk size will be generated per request from client. the web/was, image streaming, and image conversion batch modules run on EC2.

EFS: Uploaded WSI is stored and managed in EFS.

S3(optional): When you want to store and manage a large amount of WSI, it is stored and managed using S3.

RDS: Information managed on the platform and data annotated on the web are stored.